Search ga_s2am_ard_3 whole collection

The proportion (from 0 to 100) of the dataset's valid data area that contains cloud pixels. For these ARD products, this value comes from the Fmask algorithm. from:

The proportion (from 0 to 100) of the dataset's valid data area that contains cloud pixels. For these ARD products, this value comes from the Fmask algorithm. to (exclusive):

Time when dataset was created (processed) From

Time when dataset was created (processed) to (exclusive)

The raw CRS string as it appears in metadata (e.g. ‘epsg:32654’) :

One of - final|interim|nrt (near real time):

ID of a dataset type:

Ground sampling distance of the sensor’s best resolution band in metres; represents the size (or spatial resolution) of one pixel. from:

Ground sampling distance of the sensor’s best resolution band in metres; represents the size (or spatial resolution) of one pixel. to (exclusive):

The azimuth angle of the sun at the moment of acquisition, in degree units measured clockwise from due north from:

The azimuth angle of the sun at the moment of acquisition, in degree units measured clockwise from due north to (exclusive):

The elevation angle of the sun at the moment of acquisition, in degree units relative to the horizon. from:

The elevation angle of the sun at the moment of acquisition, in degree units relative to the horizon. to (exclusive):

The proportion (from 0 to 100) of the dataset's valid data area that contains clear land pixels according to the Fmask algorithm from:

The proportion (from 0 to 100) of the dataset's valid data area that contains clear land pixels according to the Fmask algorithm to (exclusive):

The proportion (from 0 to 100) of the dataset's valid data area that contains cloud shadow pixels according to the Fmask algorithm from:

The proportion (from 0 to 100) of the dataset's valid data area that contains cloud shadow pixels according to the Fmask algorithm to (exclusive):

The proportion (from 0 to 100) of the dataset's valid data area that contains clear snow pixels according to the Fmask algorithm from:

The proportion (from 0 to 100) of the dataset's valid data area that contains clear snow pixels according to the Fmask algorithm to (exclusive):

The proportion (from 0 to 100) of the dataset's valid data area that contains clear water pixels according to the Fmask algorithm from:

The proportion (from 0 to 100) of the dataset's valid data area that contains clear water pixels according to the Fmask algorithm to (exclusive):

File format (GeoTiff, NetCDF):

Mean of the absolute values of the x-axis (east-to-west) GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) from:

Mean of the absolute values of the x-axis (east-to-west) GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) to (exclusive):

Mean of the absolute values of the GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) from:

Mean of the absolute values of the GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) to (exclusive):

Mean of the absolute values of the y-axis (north-to-south) GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) from:

Mean of the absolute values of the y-axis (north-to-south) GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) to (exclusive):

Absolute value of the x-axis (east-to-west) GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) from:

Absolute value of the x-axis (east-to-west) GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) to (exclusive):

Absolute value of the total GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) from:

Absolute value of the total GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) to (exclusive):

Absolute value of the y-axis (north-to-south) GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) from:

Absolute value of the y-axis (north-to-south) GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) to (exclusive):

Circular error probable (90%) of the values of the GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) from:

Circular error probable (90%) of the values of the GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) to (exclusive):

Mean of the values of the x-axis (east-to-west) GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) from:

Mean of the values of the x-axis (east-to-west) GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) to (exclusive):

Mean of the values of the GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) from:

Mean of the values of the GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) to (exclusive):

Mean of the values of the y-axis (north-to-south) GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) from:

Mean of the values of the y-axis (north-to-south) GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) to (exclusive):

Standard Deviation of the values of the x-axis (east-to-west) GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) from:

Standard Deviation of the values of the x-axis (east-to-west) GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) to (exclusive):

Standard Deviation of the values of the GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) from:

Standard Deviation of the values of the GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) to (exclusive):

Standard Deviation of the values of the y-axis (north-to-south) GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) from:

Standard Deviation of the values of the y-axis (north-to-south) GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) to (exclusive):

Mean of the values of the x-axis (east-to-west) GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) from:

Mean of the values of the x-axis (east-to-west) GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) to (exclusive):

Mean of the values of the GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) from:

Mean of the values of the GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) to (exclusive):

Mean of the values of the y-axis (north-to-south) GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) from:

Mean of the values of the y-axis (north-to-south) GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) to (exclusive):

Standard Deviation of the values of the x-axis (east-to-west) GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) from:

Standard Deviation of the values of the x-axis (east-to-west) GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) to (exclusive):

Standard Deviation of the values of the GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) from:

Standard Deviation of the values of the GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) to (exclusive):

Standard Deviation of the values of the y-axis (north-to-south) GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) from:

Standard Deviation of the values of the y-axis (north-to-south) GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) to (exclusive):

Dataset UUID:

User who indexed the dataset:

When dataset was indexed:

Label:

Latitude range from:

Latitude range to (exclusive):

Longitude range from:

Longitude range to (exclusive):

Full metadata document:

Metadata type name of dataset:

ID of a metadata type:

Spatial reference code from the provider. For Sentinel it is MGRS code. :

The proportion (from 0 to 100) of the dataset's valid data area that contains clear land pixels according to s3cloudless from:

The proportion (from 0 to 100) of the dataset's valid data area that contains clear land pixels according to s3cloudless to (exclusive):

The proportion (from 0 to 100) of the dataset's valid data area that contains cloud land pixels according to s3cloudless from:

The proportion (from 0 to 100) of the dataset's valid data area that contains cloud land pixels according to s3cloudless to (exclusive):

Unique identifier for a datastrip relative to a given Datatake. (e.g. ‘S2A_OPER_MSI_L1C_DS_SGS__20161214T040601_S20161214T005840_N02.04’) :

ESA product URI, with the '.SAFE' ending removed. (e.g. 'S2A_MSIL1C_20220303T000731_N0400_R073_T56LNM_20220303T012845') :

Granule ID according to the ESA naming convention (e.g. ‘S2A_OPER_MSI_L1C_TL_SGS__20161214T040601_A007721_T53KRB_N02.04’) :

Acquisition time range From

Acquisition time range to (exclusive)

Dataset URI:

Add field

First 100 results (query limit)

Time (local)	Label
2015-12-27 12:04:06	ga_s2am_ard_3-2-1_50KMA_2015-12-27_final.stac-item
2016-02-12 11:56:22	ga_s2am_ard_3-2-1_50HMK_2016-02-12_final.stac-item
2016-04-10 11:16:26	ga_s2am_ard_3-2-1_51HWC_2016-04-10_final.stac-item
2016-11-05 11:39:53	ga_s2am_ard_3-2-1_50HLG_2016-11-05_final.stac-item
2017-03-29 11:26:04	ga_s2am_ard_3-2-1_51HVE_2017-03-29_final
2017-07-09 12:02:49	ga_s2am_ard_3-2-1_50KLA_2017-07-09_final
2017-07-20 11:36:04	ga_s2am_ard_3-2-1_51JUG_2017-07-20_final
2017-08-28 12:04:42	ga_s2am_ard_3-2-1_49JGL_2017-08-28_final
2017-10-07 12:03:46	ga_s2am_ard_3-2-1_49KHP_2017-10-07_final
2017-10-07 12:03:46	ga_s2am_ard_3-2-1_50KKU_2017-10-07_final
2017-12-26 12:03:42	ga_s2am_ard_3-2-1_50KMV_2017-12-26_final
2017-12-26 12:04:47	ga_s2am_ard_3-2-1_50JLQ_2017-12-26_final
2018-01-12 11:50:28	ga_s2am_ard_3-2-1_50KPF_2018-01-12_final.stac-item
2018-02-05 11:35:59	ga_s2am_ard_3-2-1_51JTF_2018-02-05_final
2018-02-05 11:35:59	ga_s2am_ard_3-2-1_51JUF_2018-02-05_final
2018-02-08 11:45:59	ga_s2am_ard_3-2-1_50HLH_2018-02-08_final
2018-02-22 11:20:58	ga_s2am_ard_3-2-1_51JXG_2018-02-22_final
2018-04-02 11:53:50	ga_s2am_ard_3-2-1_50HLG_2018-04-02_final.stac-item
2018-04-03 11:23:03	ga_s2am_ard_3-2-1_51HTC_2018-04-03_final
2018-04-23 11:17:01	ga_s2am_ard_3-2-1_51JUF_2018-04-23_final
2018-04-29 11:45:33	ga_s2am_ard_3-2-1_50JNN_2018-04-29_final
2018-05-19 11:40:33	ga_s2am_ard_3-2-1_50JNQ_2018-05-19_final
2018-05-19 11:40:33	ga_s2am_ard_3-2-1_50JPM_2018-05-19_final
2018-05-19 11:40:33	ga_s2am_ard_3-2-1_50JPN_2018-05-19_final
2018-05-22 11:53:30	ga_s2am_ard_3-2-1_50JLQ_2018-05-22_final
2018-05-22 11:53:30	ga_s2am_ard_3-2-1_50JLR_2018-05-22_final
2018-05-22 11:53:30	ga_s2am_ard_3-2-1_50JPS_2018-05-22_final
2018-05-23 11:25:37	ga_s2am_ard_3-2-1_51JVF_2018-05-23_final
2018-06-08 11:40:20	ga_s2am_ard_3-2-1_50HLG_2018-06-08_final.stac-item
2018-06-24 12:03:32	ga_s2am_ard_3-2-1_50JKP_2018-06-24_final
2018-07-08 11:40:21	ga_s2am_ard_3-2-1_50KPV_2018-07-08_final
2018-07-08 11:45:46	ga_s2am_ard_3-2-1_50HLG_2018-07-08_final.stac-item
2018-07-24 12:02:50	ga_s2am_ard_3-2-1_50JKP_2018-07-24_final
2018-07-31 11:53:40	ga_s2am_ard_3-2-1_50HLG_2018-07-31_final.stac-item
2018-08-24 11:33:07	ga_s2am_ard_3-2-1_51KUT_2018-08-24_final
2018-08-27 11:40:29	ga_s2am_ard_3-2-1_50JQS_2018-08-27_final
2018-08-31 11:24:03	ga_s2am_ard_3-2-1_51HUE_2018-08-31_final
2018-09-03 11:32:51	ga_s2am_ard_3-2-1_50HPK_2018-09-03_final
2018-09-03 11:32:51	ga_s2am_ard_3-2-1_50HQG_2018-09-03_final.stac-item
2018-09-06 11:45:53	ga_s2am_ard_3-2-1_50JNN_2018-09-06_final
2018-09-09 11:46:20	ga_s2am_ard_3-2-1_50KLU_2018-09-09_final
2018-09-30 11:24:01	ga_s2am_ard_3-2-1_51JXH_2018-09-30_final
2018-10-05 12:13:18	ga_s2am_ard_3-2-1_49KHR_2018-10-05_final
2018-10-06 11:40:38	ga_s2am_ard_3-2-1_50JNN_2018-10-06_final
2018-10-06 11:40:38	ga_s2am_ard_3-2-1_50JPS_2018-10-06_final
2018-10-09 11:51:12	ga_s2am_ard_3-2-1_50JLT_2018-10-09_final
2018-10-09 11:51:12	ga_s2am_ard_3-2-1_50KLU_2018-10-09_final
2018-10-10 11:24:31	ga_s2am_ard_3-2-1_51JVF_2018-10-10_final
2018-10-12 12:04:05	ga_s2am_ard_3-2-1_49JGM_2018-10-12_final
2018-10-12 12:04:05	ga_s2am_ard_3-2-1_50JKR_2018-10-12_final
2018-10-16 11:40:28	ga_s2am_ard_3-2-1_50KPU_2018-10-16_final
2018-10-16 11:45:53	ga_s2am_ard_3-2-1_50HMJ_2018-10-16_final
2018-10-16 11:45:53	ga_s2am_ard_3-2-1_50HPG_2018-10-16_final.stac-item
2018-10-19 11:52:28	ga_s2am_ard_3-2-1_50JLP_2018-10-19_final
2018-10-19 11:52:28	ga_s2am_ard_3-2-1_50JPS_2018-10-19_final
2018-10-20 11:23:51	ga_s2am_ard_3-2-1_51JVF_2018-10-20_final
2018-10-23 11:33:19	ga_s2am_ard_3-2-1_50JQM_2018-10-23_final
2018-10-23 11:33:19	ga_s2am_ard_3-2-1_50JQP_2018-10-23_final
2018-10-26 11:41:08	ga_s2am_ard_3-2-1_50JQP_2018-10-26_final
2018-10-26 11:41:08	ga_s2am_ard_3-2-1_50KPU_2018-10-26_final
2018-10-26 11:46:33	ga_s2am_ard_3-2-1_50HMK_2018-10-26_final
2018-11-15 11:46:50	ga_s2am_ard_3-2-1_50HMJ_2018-11-15_final
2018-11-15 11:47:04	ga_s2am_ard_3-2-1_50HMH_2018-11-15_final
2018-12-21 12:03:36	ga_s2am_ard_3-2-1_49KHS_2018-12-21_final.stac-item
2018-12-21 12:04:02	ga_s2am_ard_3-2-1_50KLV_2018-12-21_final
2018-12-21 12:04:16	ga_s2am_ard_3-2-1_50KLU_2018-12-21_final
2019-01-03 12:15:05	ga_s2am_ard_3-2-1_49JGL_2019-01-03_final
2019-01-07 11:54:28	ga_s2am_ard_3-2-1_50JPT_2019-01-07_final
2019-03-25 11:43:50	ga_s2am_ard_3-2-1_50KQA_2019-03-25_final
2019-05-23 12:13:43	ga_s2am_ard_3-2-1_49KHS_2019-05-23_final.stac-item
2020-06-01 11:27:08	ga_s2am_ard_3-2-1_51HUC_2020-06-01_final
2020-06-17 11:42:22	ga_s2am_ard_3-2-1_51KUB_2020-06-17_final.stac-item
2021-01-03 11:47:14	ga_s2am_ard_3-2-1_50HLH_2021-01-03_final
2021-03-17 11:57:22	ga_s2am_ard_3-2-1_50HLG_2021-03-17_final.stac-item
2021-04-16 11:57:14	ga_s2am_ard_3-2-1_50HMG_2021-04-16_final.stac-item
2021-04-23 11:47:20	ga_s2am_ard_3-2-1_50HMG_2021-04-23_final.stac-item
2021-04-29 12:04:22	ga_s2am_ard_3-2-1_50KLU_2021-04-29_final
2021-04-29 12:05:12	ga_s2am_ard_3-2-1_49JGL_2021-04-29_final
2021-06-05 11:57:24	ga_s2am_ard_3-2-1_50HLG_2021-06-05_final.stac-item
2021-06-15 11:54:48	ga_s2am_ard_3-2-1_50JPS_2021-06-15_final
2021-06-15 11:56:00	ga_s2am_ard_3-2-1_50JKN_2021-06-15_final
2021-06-18 12:05:16	ga_s2am_ard_3-2-1_50JKR_2021-06-18_final
2021-06-18 12:05:26	ga_s2am_ard_3-2-1_50JKQ_2021-06-18_final
2021-06-22 11:44:39	ga_s2am_ard_3-2-1_50JPT_2021-06-22_final
2021-07-12 11:44:41	ga_s2am_ard_3-2-1_50JPT_2021-07-12_final
2021-08-17 12:03:40	ga_s2am_ard_3-2-1_50KMB_2021-08-17_final
2021-08-17 12:04:01	ga_s2am_ard_3-2-1_50KKA_2021-08-17_final
2021-08-17 12:04:24	ga_s2am_ard_3-2-1_50KMU_2021-08-17_final
2021-08-17 12:04:27	ga_s2am_ard_3-2-1_50KLU_2021-08-17_final
2021-08-21 11:44:55	ga_s2am_ard_3-2-1_50JPS_2021-08-21_final
2022-02-06 12:13:39	ga_s2am_ard_3-2-1_49KHS_2022-02-06_final.stac-item
2022-02-13 12:03:44	ga_s2am_ard_3-2-1_49KHS_2022-02-13_final.stac-item
2022-06-06 12:13:50	ga_s2am_ard_3-2-1_49KHS_2022-06-06_final.stac-item
2022-07-13 12:03:57	ga_s2am_ard_3-2-1_49KHS_2022-07-13_final.stac-item
2022-07-20 11:53:15	ga_s2am_ard_3-2-1_50KQD_2022-07-20_final.stac-item
2022-09-21 12:03:52	ga_s2am_ard_3-2-1_49KHS_2022-09-21_final.stac-item
2022-10-02 11:35:41	ga_s2am_ard_3-2-1_51JTJ_2022-10-02_final.stac-item
2022-11-04 11:42:21	ga_s2am_ard_3-2-1_51KUB_2022-11-04_final.stac-item
2023-10-09 12:13:39	ga_s2am_ard_3-2-1_49KHS_2023-10-09_final.stac-item
2023-12-09 11:42:11	ga_s2am_ard_3-2-1_51KUB_2023-12-09_final.stac-item

Return to ga_s2am_ard_3 whole collection overview

ga_s2am_ard_3: Geoscience Australia Sentinel 2A MSI Analysis Ready Data Collection 3

Baseline satellite data

Inland water

Land and vegetation

Sea, ocean and coast

Hazards

Other products

All years